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Revenue maximization using adaptive resource provisioning in cloud computing environments

Citation

Feng, G and Garg, SK and Buyya, R and Li, W, Revenue maximization using adaptive resource provisioning in cloud computing environments, Proceedings of the 13th ACM/IEEE International Conference on Grid Computing 2012, 20-23 September 2012, Beijing, China, pp. 192-200. ISBN 978-1-4673-2901-9 (2012) [Refereed Conference Paper]

Copyright Statement

Copyright 2012 IEEE

DOI: doi:10.1109/Grid.2012.16

Abstract

Compared with the traditional computing models such as grid computing and cluster computing, a key advantage of Cloud computing is that it provides a practical business model for customers to use remote resources. However, it is challenging for Cloud providers to allocate the pooled computing resources dynamically among the differentiated customers so as to maximize their revenue. It is not an easy task to transform the customer-oriented service metrics into operating level metrics, and control the Cloud resources adaptively based on Service Level Agreement (SLA). This paper addresses the problem of maximizing the provider's revenue through SLA-based dynamic resource allocation as SLA plays a vital role in Cloud computing to bridge service providers and customers. We formalize the resource allocation problem using Queuing Theory and propose optimal solutions for the problem considering various Quality of Service (QoS) parameters such as pricing mechanisms, arrival rates, service rates and available resources. The experimental results, both with the synthetic dataset and with traced dadataset, show that our algorithms outperform related work.

Item Details

Item Type:Refereed Conference Paper
Keywords:cloud computing, service level agreement, resource allocation
Research Division:Information and Computing Sciences
Research Group:Distributed Computing
Research Field:Distributed and Grid Systems
Objective Division:Information and Communication Services
Objective Group:Computer Software and Services
Objective Field:Computer Time Leasing, Sharing and Renting Services
Author:Garg, SK (Dr Saurabh Garg)
ID Code:93840
Year Published:2012
Deposited By:Computing and Information Systems
Deposited On:2014-08-19
Last Modified:2014-12-08
Downloads:0

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